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sharing clinical data from neurodegenerative disease cohorts. You will be responsible for: Technically contribute and coordinate the development and implementation of data systems and analysis platforms
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datasets such as the Luxembourg Parkinson’s Study and different prodromal cohorts for neurodegenerative diseases are ready for analysis. The doctoral researcher will: Conduct research that will compose a PhD
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We seek a highly motivated bioinformatician or computational biologist who is well versed in the statistical and machine learning analysis of biomedical data and bioscientific programming for a
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Stochastic Analysis, (4) Discrete and Geometric Analysis, (5) Statistics and Data Science, and (6) Partial Differential Equations and Modelling.
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) Probability and Stochastic Analysis, (4) Discrete and Geometric Analysis, (5) Statistics and Data Science, and (6) Partial Differential Equations and Modelling. The Faculty of Science, Technology and Medicine
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recognized for our GDPR compliant data hosting solutions and data management systems. We develop innovative methodologies for data mining, federated data analysis, and data FAIRification. We strongly advocate
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Organize and prepare content/analysis for project events, such as stakeholder meetings and policy briefs Network with researchers and stakeholders to support the development of the project Engage in outreach
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into cross-seeding between microbiome-borne amyloidogenic proteins and human proteins implicated in neurodegenerative disea Your responsibilities: The doctoral candidate will perform computational analysis
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Research Group. Tasks: Conduct and co-lead quantitative research within large-scale mixed-methods projects Contribute to and coordinate primary data collection and analysis (e.g. surveys, survey experiments
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for the HBSC project Contribute to the quantitative analysis of the Luxembourgish HBSC 2022 data Contribute to the preparation of the Luxembourgish HBSC 2026 survey Contribute to the preparation of the National